Accompanying the rapid growth in the amount of information available in the form of documents stored in databases has come an increased need to efficiently extract information relevant to a specific need. Traditional searching methods search and retrieve documents according to the words in a given input query. Search engines allow users to find documents containing one or more words or phrases, often referred to as keywords, found in the input query and return a list of relevant documents for the input query. For instance, with traditional search and retrieval methods, the input query                Time Warner        
returns a list of documents containing one or both words Time or Warner. Search engines may also permit the formulation of Boolean queries, which allow words in the query to be combined using logical operations such as AND, OR, and NOT. Such operations allow to specify which words must appear in the documents, which words may appear in the documents, and which words may not appear in the documents. For example, using a traditional Boolean search engine, the query                US AND OPEN AND (NOT golf)        
selects documents that contain the word US and Open but not the word golf
Another feature that may be used when performing queries with traditional search engines is the ability to trigger a search for phrases in documents. For example the query                “US Open”        
retrieves documents that contain the exact phrase “US Open” while rejecting documents that contain the word US and/or the word Open separately. Examples of search engines offering these capabilities are search engines used with the World Wide Web such as AltaVista™, Lycos™, Inktomi™, InfoSeek™, NorthernLight™, HotBot™, MSN Search™, Google™ and Yahoo™. Additional search engines include those used for searching documents found in databases, digital libraries or other information sources such as Inktomi Enterprise Search™, Verity™, K2 Enterprise, or AltaVista® Search Software.
The result of a search using search engines such as those mentioned above is a list of relevant documents, generally displayed in some order, for example, from the most relevant document to the least relevant document. To present documents in an order, search engines rank the documents according to some metric. Typically, the ranking will first show documents containing the highest number of keywords.
For example, referring to FIG. 1, screen display 10 shows the result of a search on Google™ (http://www.google.com) for the query Time Warner. The screen display 10 shows the first 3 documents ranked from the most relevant document to the least relevant document. Each of the results consists of a description of a document. Such description, for example, may include the title of the document, a description of the document, and its Internet Uniform Resource Locator (URL).
One form of output of traditional search engines that may be queried are documents which match words in the input query. Although documents may be what users are seeking when using traditional search engines, it may also be that a user is seeking information other than document names or URLs.
For example, as illustrated in the screen display 20 of FIG. 2, a user who is seeking the names of tennis players who won the US Open tournaments, may issue the query                tennis US Open winners        
The above-referenced query may be an input query to a traditional search engines which display as query results the documents including words from the input query. It may be the case that the user is looking for the actual names of tennis players who won the US Open.
As another example, as illustrated in the screen display 30 of FIG. 3, a user seeking the movie titles in which Bruce Willis appears may issue the query Bruce Willis movies. As shown in screen display 30, a traditional search engine may return as a query result the documents in which the input query terms appear rather than the movie titles. Screen display 40 of FIG. 4 also illustrates the return of documents in response to an input query of Oregon senators.
In the foregoing description as illustrated in the screen displays 10, 20, 30 and 40, conventional search engines and World Wide Web search engines expect that the user is seeking documents that include particular term or terms of an input query. It may be desirable to provide a search engine, for example, with the ability to return information besides documents and to infer additional information that a user may be seeking based on a particular input query.
For example, when a user issues the query tennis US Open winners, the user may be seeking the names of the tennis players who won the US Open. Traditional search engines are unable to recognize that a user is seeking the names of tennis players and not looking for documents including the terms from the input query. Similarly, the query Oregon senators, may be intended to seek the names of senators of Oregon and not to seek documents. As yet another example used above, when a user issues the query Bruce Willis movies, the user may not be looking for the actual documents including input query terms, but may rather be looking for the titles of movies in which Bruce Willis appears.
Question-answering systems, for example, such as described in pending U.S. patent application Ser. No. 09/845,571, filed Apr. 30, 2001, entitled SYSTEM FOR ANSWERING NATURAL LANGUAGE QUESTIONS, (hereinafter “the Question Answering application”), may be used to provide answers to questions. However, the foregoing systems expect input in the form of a question. For example, a user seeking for the names of senators of Oregon, may issue the question
Who are the senators of Oregon?
Although question-answering systems will give the names of senators of Oregon as results, the user is expected to type a question and is unable to issue a short and simple query as senators of Oregon.
The foregoing question-answering systems may suffer from a drawback in that the user is expected to input a question, and may not accept as input short queries which do not form a question. Furthermore, users of traditional search engines and systems may be more inclined to type short keyword queries (e.g., one, two or at most three words) than to enter input queries in the form of questions which may be much longer (e.g., more than five words).
It may also be desirable to have a system and method for inferring additional information from a query and provide as output answers in response to the inferred additional information. It may also be desirable to provide the document lists produced in accordance with the original input query terms. It may also be desirable to provide document lists in accordance with terms of the inferred information.